Resolving Contradictions in Medical Technology

R&D professionals regularly encounter contradictory requirements as a matter of course in almost every innovation program.  Increasing the performance of one parameter is directly correlated with a decrease in performance of another important system parameter.  These contradictions can become the bane of breakthrough results if they are addressed inadequately or not at all.  Researchers often resort to optimizing the system as a useful compromise, using a highly iterative procedure.  Optimization is viewed as the means to balanced performance outcomes.

Yet, sometimes the performance compromise can relate to life-critical parameters – a scenario faced by medical device R&D scientists and engineers.  In healthcare, novel devices are expected to meet diverse and increasingly stringent requirements where dependability and performance can be life-critical.  Medical device companies use a validation plan to define process or product requirements in terms of test criteria, calibration and maintenance requirements, cleanliness requirements, particle count criteria, etc.

But what if the new product has contradictory requirements?  For example, a catheter may need high tensile strength for pressure infusion tests, but increased strength causes poor performance on mandatory flex test requirements important to guiding the device through an artery.  This contradiction – the device must be strong enough and at the same time flexible – presents a major hurdle to meeting critical validation elements.  Optimization is either not possible or would lead to a compromise with unacceptable outcomes.

Instead, contradictions can be resolved using simple tools and without compromise-based design methods.   For example, one efficient approach is to satisfy both sides of a contradiction by separating requirements in time or space and then solving for each requirement at different moments of time, or for different parts of the object, or at different sections of its non-linear characteristic.

An important step to resolving contradictions is to reframe the initial problem from the outset.  For instance, instead of trying to synthesize an optimal material for the whole catheter, a designer can specify different requirements to different sections of the device.  By listing contradictory requirements and indicating to which parts of the object / moments of time / stages of its life cycle they apply, solutions become clear and a pathway forward can be developed.  A precise and reframed problem statement is essential for developing solutions using a limited set of separation principles.

In summary, contradictions are sometimes obvious, sometimes hidden barriers that exist within most engineered systems.  Taking the time and care to unearth them, understand their nature, isolate/exaggerate specific requirements, and then solve for them – rather than optimizing against them – can spell the difference between average products and breakthrough (even life-saving) innovations.

When Open Innovation Programs Fail

Since the introduction of Open Innovation (“OI”) over a decade ago, companies have been opening their doors to new forms of collaboration and information access.  Indeed, staying competitive in an environment of rapid technological change and evolving consumer preferences has demanded that companies rethink the traditional boundaries of the R&D center.  The logic is compelling:  gain competitive advantage by reaching beyond traditional domains, conceiving multi-disciplinary solutions, and accelerating development cycle times.

Yet, too often, Open Innovation results fall far short of the promised benefits.  But, why?  No one doubts the potential of a world of expanded (if not infinite) knowledge.  Further, sophisticated digital and networking tools have enabled almost universal access to this knowledge.

But a closer look reveals that the problems associated with OI performance often lie with the processes of how companies execute OI programs, not with the fundamental tenets of Open Innovation itself.  Indeed, experience tells us that certain practices can lead to poor OI performance:

“Big Net” Fallacy. Operating under the premise that “the bigger the net, the bigger the prize”, OI initiatives can yield too much information and not enough knowledge.

Accordingly, discipline is essential to an effective OI program that targets quality over quantity.  Time spent on precise and insightful problem framing will give positive returns in the form of less noise and fewer resources needed to process search results.

Support Staff Model. Some OI organizations have been given a mandate, but no organizational buy-in to effect change.

Traditional support staff models are designed for required or regulated functions (e.g., legal, accounting, regulatory affairs, safety).  Their costs are then allocated to the businesses they serve.  Effective OI initiatives should instead deploy a free market model to service delivery, where understanding and responding to stakeholder needs is paramount.  In-house OI services are better “purchased”, rather than allocated.

Job for a Few. Thinking of OI as someone else’s job tends to create bureaucracies that add organizational cost, without delivering results.

OI must become a mindset for all employees, not just a job for a selected few; in-house OI professionals must be facilitators, coaches, and leaders to effect organizational transformation.

Square Peg, Round Hole. Companies design broad-reaching OI strategies without recognizing and accounting for the organizational barriers that can (and will) derail the best laid plans.

Effective OI programs must have an ability to monitor, measure, and correct where necessary.  And, metrics must be aligned with business metrics to avoid misaligned incentives, which can thwart progress and prevent acceptable returns on OI investment.

Three Traps That Can Derail Technology Scouting Efforts

In a world of seemingly infinite knowledge, technology scouting holds great promise for companies looking to discover and unlock new sources of economic value.  Innovation programs depend on scouting efforts to find enabling technologies that are actionable and pragmatic.  Yet, too often, tech scouting produces a lot of information, but no clear path for moving forward.  Low internal adoption rates may result from:

  • Too many choices and an inability to sort through mountains of information
  • A disconnect between the surfaced technologies and the problems that need to be solved
  • A mismatch between existing in-house capabilities and the resources needed to adopt and develop selected new technologies
  • Longer development time horizons that do not meet a need for near-term solutions
  • An inability to secure business commitment because of unclear (or weak) alignment with market needs.

These factors often present significant barriers for effective technology scouting programs.

 Avoiding Traps

Three common traps that hinder technology scouting efforts:

Imprecise Problem Framing. A poorly framed problem can diminish results, before the search is even underway.  In short, you cannot find what you are looking for if you don’t know where to look.  The most effect problem statements have a clear line of sight to market needs and reflect deeply rooted problems that hinder current system performance.  These deeply rooted problems become the guideposts for effective external search.  Their absence can lead to misguided efforts.

Unrealistic Expectations.  Searching for “plug ‘n play” solutions, which in many cases do not exist, can lead to disappointing results.  A pragmatic understanding of the adaptation requirements and associated time horizons is essential for effective scouting.  In addition, sometimes companies define search outcomes in terms of potential development partners.  Instead, the identification of partners should more logically come toward the end of a scouting program, once candidate technologies have been selected.  Only then will it be clear as to what type of partners to search for (academic research, equipment companies, materials providers, SME’s, CRO’s, etc).

Inability to Interpret Results.  Too much information and not enough insight leaves companies stuck on where to go next.  It is essential to develop evaluation criteria that are linked both to performance parameters and the adaptation requirements needed for adoption.  Technologies cannot be considered in isolation.  This requires a realistic (and creative) view on how the technology will manifest in a product and the problems that must be overcome to adopt it into the target system.

Gen5 adheres to three guiding principles to help clients avoid the traps that can derail effective technology scouting efforts.

Technology Incubation – A New Model for Corporate R&D

Corporate R&D is under mounting pressure to keep pace with technological advancement that is moving at record speed and a shifting competitive landscape where innovation increasingly occurs in startups outside of the corporate R&D center. Further complicating matters, in the digital era, breakthrough innovations are as much about business model innovation as they are technical innovation.

In this environment, it is a challenge for R&D simultaneously to support the enterprise’s global businesses, while also pushing to find and deliver the “next big thing”, which in many cases would likely represent a disruption to the core business. Accordingly, today companies are looking both internally and externally for ways to remain competitive in a technology market that is no longer the exclusive domain of corporate giants.

Corporate R&D is equipped with well-developed processes, structure, and culture which have evolved over time to effectively support the core business. But, this infrastructure and the accompanying measurement systems become an albatross for R&D when attempting to develop concepts that lie outside of the company’s business model and/or beyond its core technical expertise. A modified approach – technology incubation – blending both service model and investment model techniques, will better enable corporate R&D to compete in a rapidly changing, fast-paced marketplace for commercializing (or monetizing) breakthrough opportunities.

Download White Paper

Another Voice – Uncovering New Sources of Customer Value

If your product could speak, what would it say? If your system was hiding sources of customer value, how would you know it? If your customers could inquire about technologies beyond their understanding, what would they ask for?

The Voice of the Product (VOP) is a powerful means for uncovering new sources of customer value as targets for disruptive product innovation. Used as a complement to Voice of the Customer (VOC) techniques, VOP entails a deliberate and structured review of a product’s system and surrounding environment to reveal unexploited resources and functionality.

Because innovation is ultimately about value creation – not invention – it is essential that product innovation efforts focus explicitly on meeting the specific customer needs that drive purchase decisions. Uncovering these essential needs, or Main Parameters of Value (MPV’s), is a prerequisite for any effective innovation program. Of course, the most straightforward method for discerning market requirements is to survey target customers directly. Indeed, well-developed qualitative and quantitative VOC research techniques are commonly used for securing market insights. Yet an exclusive reliance on customer interviewing can be limiting and risks missing out on hidden opportunities. It is very difficult (if not impossible) for customers to express a desire for things that they don’t know about or don’t believe are technically possible.

To get around this problem, a diagnostic approach called Voice of the Product can be used to uncover new, unexploited sources of customer value. VOP analysis mines for unknown sources of value by “interviewing” the product (through its functions), industry (through patents), and future (through technology trends).

Product – By systematically mapping all functional interactions among a product and its surroundings, the VOP functional lens can uncover unexploited functionality that resides in a system, yet may not be expressed through current product features and functionality.

Industry – Patent analysis can be a useful proxy for uncovering additional market needs already being addressed by other market participants, as well as unearthing white spaces with minimal market activity.

Future – Finally, by considering how systems may evolve into the future, additional new sources of customer value may surface. Systems evolve predictably over time in a bid to bring more value to the marketplace. Objective technology trends propel a system’s evolution, typically along an S-curve pattern or prompting a migration to the next S-curve for a given target parameter. While these trends do not provide ready-made solutions, they are used to prompt thinking on how to uncover and consider new dimensions of innovation.

By leveraging Voice of the Product analysis, R&D can take a proactive role in setting a corporate innovation agenda that is tightly aligned with market needs and capable of fueling growth. VOP analysis can uncover latent user needs that become targets for innovation investment. Combining VOP with VOC techniques can yield a more robust innovation program.

Systematic Innovation – The Discipline behind Breakthrough Ideas

Over the past decade, business leaders have become convinced of the need to extend the reach of R&D beyond the corporate center. However, in the chase to find externally sourced solutions, companies have repeatedly failed to realize the promised benefits of going outside. Simply running faster and “throwing more darts” is akin to hoping to win the lottery. Further, thinking of this as someone’s “job” tends to create bureaucracies that add organizational cost, without delivering results.

Even though information is becoming infinite, knowledge and insight often lags behind. Although digital technologies can enable access to resources and information in ways that were previously unheard of, this environment sometimes fuels a corporate optimism that supersedes pragmatism. Too often, searching for a solution boils down to luck and information overload becomes an unproductive drain on resources.

Realistically speaking, it is not possible to boil the ocean before running out of time, money, and patience. The challenge for the corporate R&D center is one of risk management. Delivering against return on investment requirements demands processes that are systematic and repeatable. Yet this demand for discipline must accommodate a world that is more complex, interdisciplinary, and moving at ever increasing speed. As a result, it is not about getting more chances, but rather about having better aim.

A fundamentally different philosophy and a more systematic and scientific approach are needed. Often, it is not about finding a complete plug-and-play solution, but rather identifying the best Lego blocks to fit the target system. Further, the goal is to build skills among all employees, not create jobs for a selected few.

A disciplined approach relies on specific tools for breaking down a system into its underlying root cause problems. These tools help to uncover the “right” problems to be solved and reveal insights on what altitude is most practical for solving them. Importantly, the approach reveals insights not only on where to look, but also what to look for in terms of knowledge, technologies, or solutions. And, because a common functional language is used to link the initial system with the external system, the adaptation requirements become much more visible – a critical element for commercialization.

The goal of a systematic approach is to achieve greater focus at each stage of the innovation process and uncover new opportunities to exploit – but in a deliberate, not random, way. Fundamental tenets:

  • Right Target – Understand the most important sources of customer value and maintain a relentless focus on these value parameters.
  • Right Altitude – Consider the most appropriate level for articulating the problem and applying innovation resources, e.g., at the system, component, or sub-system level.
  • Right Problem – Ensure a precise understanding of the fundamental problem that needs to be solved to improve system performance. Avoid working on surface level problems that may in fact be symptoms of deeper rooted physical problems.
  • Right Solution – Avoid the temptation to always invent. Find and adapt enabling technologies and/or leverage existing solutions that can reduce development cycle time and cost.

The Next Generation

Given dramatic shifts in the pace and complexity of technology advancement, it has become increasingly evident that corporations need a more flexible, agile, and predictable means for identifying and capturing new, profitable growth opportunities.

Accordingly, GEN3 Partners restructured its business to better align its resources with a changing landscape in technology and innovation.  The company leveraged the IPO of Airgain, one of its home grown ventures, and the sale of its share in Healbe, another startup based on GEN3 technology, as an opportunity to recalibrate and reinvest.

As of September 1, 2016, the core of the innovation practice of GEN3 Partners began operating as a new company, Gen5 Group.   Gen5 still brings the technical creativity that has been a hallmark of its past success, but with a greater emphasis on value creation.  Leveraging its venture experience, the new company is migrating from a traditional consulting model to more of a technology incubation model for corporate clients.